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Kajian serba linguistik

untuk Anton Moeliono, pereksa bahasa

Languages, linguistics, and civilization; festschrift in honor of Anton Moeliono, Indonesian expert in linguistics.

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Profiles in Operations Research

Pioneers and Innovators

Profiles in Operations Research: Pioneers and Innovators recounts the development of the field of Operations Research (OR), the science of decision making. The book traces the development of OR from its military origins to a mature discipline that is recognized worldwide for its contributions to managerial planning and complex global operations. Over the past six decades, OR analyses have impacted our daily lives: when making an airline or hotel reservation, waiting in line at a bank, getting the correctly blended fuel at the gas station, and ensuring that the book you are holding arrived at its destination on time. OR originated in the late 1930s when British scientists from various disciplines joined Royal Air Force officers to determine the most effective way to employ new radar technology for intercepting enemy aircraft. During World War II, similar applied research groups were formed to study, test, and evaluate military operations on both sides of the Atlantic. Their work resulted in great improvements—OR helped the Allies win the war. The scientific field that emerged from these studies was called operational research in the U.K. and operations research in the U.S. Today, OR provides a broad and powerful science to aid decision making. Profiles describes the lives and contributions of 43 OR pioneers and innovators and relates how these individuals, with varying backgrounds and diverse interests, were drawn to the nascent field of OR. The profiles also describe how OR techniques and applications expanded considerably beyond the military context to find new domains in business and industry. In addition to their scientific contributions, these profiles capture the life stories of the individuals—interwoven with personal tales, vivid vignettes, family backgrounds, and views of the mission and future of OR. Collectively, the profiles recount the fascinating story of the growth and development of a field enriched by the convergence of different disciplines. The Editors: Arjang A. Assad is Dean of the School of Management, University at Buffalo, State University of New York. Saul I. Gass is Professor Emeritus, Department of Decision, Operations & Information Technologies, Smith School of Business, University of Maryland, College Park. From the Reviews Profiles In Operations Research: Pioneers and Innovators. Book Review by Nigel Cummings: U.K. OR Society's e-journal, Inside OR., Sept 2011. "I can thoroughly recommend this book. I found it both enlighteningand undeniably gripping, so much so in fact, you may find it difficultto put it down once you have commenced reading it. Arjang A. Assad and Saul I. Gass have created a masterwork whichwill serve to immortalise [stet] the pioneers of O.R. for many years to come." *For a list of all known typos, plus further discussion on the book, please visit

he founders of operations research (OR) all trained and practiced in Saul was
among the first OR professionals having become a member of the Operations
Research Society of America (ORSA) in 1954.

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.

Schaal, S.: Is Imitation Learning the Route to Humanoid Robots? Trends in
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